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<a href="_c_v_dataset_tools_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">//===========================================================================</span><span class="comment"></span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> *</span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> *</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * \brief       Tools for cross-validation</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> *</span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> *</span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> *</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> * \author      O.Krause</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> * \date        2010-2012</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> *</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> *</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> *</span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> *</span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published</span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> *</span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> *</span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment"> *</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="comment"> */</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="comment">//===========================================================================</span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span> </div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="preprocessor">#ifndef SHARK_DATA_CVDATASETTOOLS_H</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span><span class="preprocessor">#define SHARK_DATA_CVDATASETTOOLS_H</span></div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span> </div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="preprocessor">#include &lt;<a class="code" href="_dataset_8h.html">shark/Data/Dataset.h</a>&gt;</span></div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="preprocessor">#include &lt;<a class="code" href="_random_8h.html">shark/Core/Random.h</a>&gt;</span></div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="preprocessor">#include &lt;algorithm&gt;</span></div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="preprocessor">#include &lt;<a class="code" href="_data_view_8h.html">shark/Data/DataView.h</a>&gt;</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span> </div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span><span class="preprocessor">#include &lt;utility&gt;</span> <span class="comment">//for std::pair</span></div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span> </div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span> </div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span> </div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> DatasetTypeT&gt;</div>
<div class="foldopen" id="foldopen00049" data-start="{" data-end="};">
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html">   49</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds</a> {</div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#a34e7cbd1c1ee70e1052194320e946574">   51</a></span>    <span class="keyword">typedef</span> DatasetTypeT <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#a34e7cbd1c1ee70e1052194320e946574">DatasetType</a>;</div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#aefd7fec613275b78bcc1eedfc0694b2f">   52</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> DatasetType::IndexSet <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#aefd7fec613275b78bcc1eedfc0694b2f">IndexSet</a>;</div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span><span class="comment"></span> </div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span><span class="comment">    /// \brief Creates an empty set of folds.</span></div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#ad1e48f9176458dbb2d1229219baafbed">   55</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_c_v_folds.html#ad1e48f9176458dbb2d1229219baafbed" title="Creates an empty set of folds.">CVFolds</a>() {}<span class="comment"></span></div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="comment">    ///\brief partitions set in validation folds indicated by the second argument.</span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span><span class="comment">    /// The folds are given as the batch indices of the validation sets</span></div>
<div class="foldopen" id="foldopen00059" data-start="{" data-end="}">
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#aca57fb2a330236dca37fa47240e89a22">   59</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_c_v_folds.html#aca57fb2a330236dca37fa47240e89a22" title="partitions set in validation folds indicated by the second argument.">CVFolds</a>(</div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span>        <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#a34e7cbd1c1ee70e1052194320e946574">DatasetType</a> <span class="keyword">const</span> &amp;set,</div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span>        std::vector&lt;IndexSet&gt; <span class="keyword">const</span> &amp;validationIndizes</div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span>    ) : m_dataset(set),m_validationFolds(validationIndizes) {}</div>
</div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span>    </div>
<div class="foldopen" id="foldopen00064" data-start="{" data-end="}">
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#a5c977743c718d50db3fdf76741ffbbdd">   64</a></span>    <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a5c977743c718d50db3fdf76741ffbbdd">CVFolds</a>(</div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span>        <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#a34e7cbd1c1ee70e1052194320e946574">DatasetType</a> <span class="keyword">const</span> &amp;set,</div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno">   66</span>        std::vector&lt;std::size_t&gt; <span class="keyword">const</span> &amp;foldStart</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span>    ) : m_dataset(set){</div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span>        <span class="keywordflow">for</span> (std::size_t partition = 0; partition != foldStart.size(); partition++) {</div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span>            std::size_t partitionSize = (partition+1 == foldStart.size()) ? set.numberOfBatches() : foldStart[partition+1];</div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno">   70</span>            partitionSize -= foldStart[partition];</div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno">   71</span>            <span class="comment">//create the set with the indices of the validation set of the current partition</span></div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span>            <span class="comment">//also update the starting element</span></div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span>            <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#aefd7fec613275b78bcc1eedfc0694b2f">IndexSet</a> validationIndizes(partitionSize);</div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span>            <span class="keywordflow">for</span> (std::size_t batch = 0; batch != partitionSize; ++batch) {</div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span>                validationIndizes[batch]=batch+foldStart[partition];</div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno">   76</span>            }</div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span>            m_validationFolds.push_back(validationIndizes);</div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span>        }</div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span>    }</div>
</div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span> </div>
<div class="foldopen" id="foldopen00081" data-start="{" data-end="}">
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#a71a49586552161e0027348fa3a165310">   81</a></span>    <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#a34e7cbd1c1ee70e1052194320e946574">DatasetType</a> <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a71a49586552161e0027348fa3a165310">training</a>(std::size_t i)<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(i &lt; <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a55e4d73aff1389cb61fc9e41fc1e92ee" title="Returns the number of folds of the dataset.">size</a>());</div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span>        <span class="keywordflow">return</span> m_dataset.indexedSubset(<a class="code hl_function" href="classshark_1_1_c_v_folds.html#a04f39c269ed88cf04953269a022f925a">trainingFoldIndices</a>(i));</div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span>    }</div>
</div>
<div class="foldopen" id="foldopen00085" data-start="{" data-end="}">
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#a02f53dc5f3585ac17b190bbbe9549b88">   85</a></span>    <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#a34e7cbd1c1ee70e1052194320e946574">DatasetType</a> <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a02f53dc5f3585ac17b190bbbe9549b88">validation</a>(std::size_t i)<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(i &lt; <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a55e4d73aff1389cb61fc9e41fc1e92ee" title="Returns the number of folds of the dataset.">size</a>());</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>        <span class="keywordflow">return</span> m_dataset.indexedSubset(<a class="code hl_function" href="classshark_1_1_c_v_folds.html#ab2345d3eba31a6b7d4d47cd8e0e6f6e7" title="returns the indices that make up the i-th validation fold">validationFoldIndices</a>(i));</div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span>    }</div>
</div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span><span class="comment"></span> </div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span><span class="comment">    ///\brief returns the indices that make up the i-th validation fold</span></div>
<div class="foldopen" id="foldopen00091" data-start="{" data-end="}">
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#ab2345d3eba31a6b7d4d47cd8e0e6f6e7">   91</a></span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#aefd7fec613275b78bcc1eedfc0694b2f">IndexSet</a> <span class="keyword">const</span> &amp;<a class="code hl_function" href="classshark_1_1_c_v_folds.html#ab2345d3eba31a6b7d4d47cd8e0e6f6e7" title="returns the indices that make up the i-th validation fold">validationFoldIndices</a>(std::size_t i)<span class="keyword">const </span>{</div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(i &lt; <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a55e4d73aff1389cb61fc9e41fc1e92ee" title="Returns the number of folds of the dataset.">size</a>());</div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span>        <span class="keywordflow">return</span> m_validationFolds[i];</div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span>    }</div>
</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span>    </div>
<div class="foldopen" id="foldopen00096" data-start="{" data-end="}">
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#a04f39c269ed88cf04953269a022f925a">   96</a></span>    <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#aefd7fec613275b78bcc1eedfc0694b2f">IndexSet</a> <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a04f39c269ed88cf04953269a022f925a">trainingFoldIndices</a>(std::size_t i)<span class="keyword">const </span>{</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(i &lt; <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a55e4d73aff1389cb61fc9e41fc1e92ee" title="Returns the number of folds of the dataset.">size</a>());</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span>        <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#aefd7fec613275b78bcc1eedfc0694b2f">IndexSet</a> trainingFold;</div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span>        detail::complement(m_validationFolds[i], m_dataset.numberOfBatches(), trainingFold);</div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span>        <span class="keywordflow">return</span> trainingFold;</div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>    }</div>
</div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span><span class="comment"></span> </div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span><span class="comment">    ///\brief Returns the number of folds of the dataset.</span></div>
<div class="foldopen" id="foldopen00104" data-start="{" data-end="}">
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#a55e4d73aff1389cb61fc9e41fc1e92ee">  104</a></span><span class="comment"></span>    std::size_t <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a55e4d73aff1389cb61fc9e41fc1e92ee" title="Returns the number of folds of the dataset.">size</a>()<span class="keyword">const </span>{</div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span>        <span class="keywordflow">return</span> m_validationFolds.size();</div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>    }</div>
</div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span><span class="comment"></span> </div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span><span class="comment">    /// \brief Returns the dataset underying the folds</span></div>
<div class="foldopen" id="foldopen00109" data-start="{" data-end="}">
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#ad0bbe71a5ab3021ec9b6e43d7b6555fd">  109</a></span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#a34e7cbd1c1ee70e1052194320e946574">DatasetType</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_c_v_folds.html#ad0bbe71a5ab3021ec9b6e43d7b6555fd" title="Returns the dataset underying the folds.">dataset</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>        <span class="keywordflow">return</span> m_dataset;</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span>    }</div>
</div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span>    <span class="comment"></span></div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span><span class="comment">    /// \brief Returns the dataset underying the folds</span></div>
<div class="foldopen" id="foldopen00114" data-start="{" data-end="}">
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno"><a class="line" href="classshark_1_1_c_v_folds.html#a523c99e2d2843046e679990653983839">  114</a></span><span class="comment"></span>    <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#a34e7cbd1c1ee70e1052194320e946574">DatasetType</a>&amp; <a class="code hl_function" href="classshark_1_1_c_v_folds.html#a523c99e2d2843046e679990653983839" title="Returns the dataset underying the folds.">dataset</a>(){</div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>        <span class="keywordflow">return</span> m_dataset;</div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span>    }</div>
</div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span> </div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span>    <a class="code hl_typedef" href="classshark_1_1_c_v_folds.html#a34e7cbd1c1ee70e1052194320e946574">DatasetType</a> m_dataset;</div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>    std::vector&lt;IndexSet&gt; m_validationFolds;</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>    std::size_t m_datasetSize;</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>    std::vector&lt;std::size_t&gt; m_validationFoldSizes;</div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>};</div>
</div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span> </div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span><span class="comment"></span> </div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span><span class="comment">/// auxiliary typedef for createCVSameSizeBalanced and createCVFullyIndexed, stores location index in the first and partition index in the second</span></div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno"><a class="line" href="namespaceshark.html#a26c31934671564b8b69e260e23be0b90">  127</a></span><span class="comment"></span><span class="keyword">typedef</span> std::pair&lt; std::vector&lt;std::size_t&gt; , std::vector&lt;std::size_t&gt; &gt; <a class="code hl_typedef" href="namespaceshark.html#a26c31934671564b8b69e260e23be0b90" title="auxiliary typedef for createCVSameSizeBalanced and createCVFullyIndexed, stores location index in the...">RecreationIndices</a>;</div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span> </div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span><span class="keyword">namespace </span>detail {</div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span><span class="comment"></span> </div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span><span class="comment">///\brief Version of createCVSameSizeBalanced which works regardless of the label type</span></div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span><span class="comment">///</span></div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span><span class="comment">/// Instead of a class label to interpret, this class uses a membership vector for every</span></div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span><span class="comment">/// class which members[k][i] returns the positon of the i-th member of class k in the set.</span></div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> I, <span class="keyword">class</span> L&gt;</div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span><a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt; createCVSameSizeBalanced(</div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;</a> &amp;set,</div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span>    std::size_t numberOfPartitions,</div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span>    std::vector&lt; std::vector&lt;std::size_t&gt; &gt; members,</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>    std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>,</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>    <a class="code hl_typedef" href="namespaceshark.html#a26c31934671564b8b69e260e23be0b90" title="auxiliary typedef for createCVSameSizeBalanced and createCVFullyIndexed, stores location index in the...">RecreationIndices</a> * cv_indices = NULL <span class="comment">//if not NULL: the first vector stores location information, and</span></div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>                      <span class="comment">// the second the partition information. The i-th value of the</span></div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span>                      <span class="comment">// first vector shows what the original position of the now i-th</span></div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>                      <span class="comment">// sample was. The i-th value of the second vector shows what</span></div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span>                      <span class="comment">// partition that sample now belongs to.</span></div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span>) {</div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span>    std::size_t numInputs = set.<a class="code hl_function" href="group__shark__globals.html#ga5333445992cd6b14392cd80a1ab5403c" title="Returns the total number of elements.">numberOfElements</a>();</div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span>    std::size_t numClasses = members.size();</div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span> </div>
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno">  150</span>    <span class="comment">//shuffle elements in members</span></div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span>    <span class="keywordflow">for</span> (std::size_t c = 0; c != numClasses; c++) {</div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>        std::shuffle(members[c].begin(), members[c].end(), <a class="code hl_variable" href="namespaceshark_1_1random.html#ab5c1547eee483974d008d43f621a2234">random::globalRng</a>);</div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span>    }</div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span> </div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span>    <span class="comment">//calculate number of elements per validation subset in the new to construct container</span></div>
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno">  156</span>    std::size_t nn = numInputs / numberOfPartitions;</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>    std::size_t leftOver = numInputs % numberOfPartitions;</div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span>    std::vector&lt;std::size_t&gt; validationSize(numberOfPartitions,nn);</div>
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno">  159</span>    <span class="keywordflow">for</span> (std::size_t partition = 0; partition != leftOver; partition++) {</div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span>        validationSize[partition]++;</div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span>    }</div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span> </div>
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno">  163</span>    <span class="comment">//calculate the size of the batches for every validation part</span></div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span>    std::vector&lt;std::size_t&gt; partitionStart;</div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span>    std::vector&lt;std::size_t&gt; batchSizes;</div>
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno">  166</span>    std::size_t numBatches = batchPartitioning(validationSize,partitionStart,batchSizes,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>);</div>
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno">  167</span> </div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span> </div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;</a> newSet(numBatches);<span class="comment">//set of empty batches</span></div>
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno">  170</span>    <a class="code hl_class" href="classshark_1_1_data_view.html" title="Constant time Element-Lookup for Datasets.">DataView&lt;LabeledData&lt;I,L&gt;</a> &gt; setView(set);<span class="comment">//fast access to single elements of the original set</span></div>
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno">  171</span>    std::vector&lt;std::size_t&gt; validationSetStart = partitionStart;<span class="comment">//current index for the batch of every fold</span></div>
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno">  172</span>    <span class="comment">//partition classes into the validation subsets of newSet</span></div>
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno">  173</span>    std::size_t fold = 0;<span class="comment">//current fold</span></div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno">  174</span>    std::vector&lt;std::vector&lt;std::size_t&gt; &gt; batchElements(numberOfPartitions);</div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span> </div>
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno">  176</span>    <span class="comment">//initialize the list of position indices which can later be used to re-create the fold (via createCV(Fully)Indexed)</span></div>
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno">  177</span>    <span class="keywordflow">if</span> ( cv_indices != NULL ) {</div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span>        cv_indices-&gt;first.clear();</div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span>        cv_indices-&gt;first.resize( numInputs );</div>
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno">  180</span>        cv_indices-&gt;second.clear();</div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span>        cv_indices-&gt;second.resize( numInputs );</div>
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno">  182</span>    }</div>
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno">  183</span> </div>
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno">  184</span>    <span class="keywordtype">size_t</span> j = 0; <span class="comment">//for recreation indices</span></div>
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno">  185</span>    <span class="keywordflow">for</span> (std::size_t c = 0; c != numClasses; c++) {</div>
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno">  186</span>        <span class="keywordflow">for</span> (std::size_t i = 0; i != members[c].size(); i++) {</div>
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno">  187</span>            std::size_t oldPos = members[c][i];</div>
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno">  188</span>            std::size_t batchNumber = validationSetStart[fold];</div>
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno">  189</span> </div>
<div class="line"><a id="l00190" name="l00190"></a><span class="lineno">  190</span>            batchElements[fold].push_back(oldPos);</div>
<div class="line"><a id="l00191" name="l00191"></a><span class="lineno">  191</span> </div>
<div class="line"><a id="l00192" name="l00192"></a><span class="lineno">  192</span>            <span class="keywordflow">if</span> ( cv_indices != NULL ) {</div>
<div class="line"><a id="l00193" name="l00193"></a><span class="lineno">  193</span>                cv_indices-&gt;first[ j ] = oldPos; <span class="comment">//store the position in which the (now) i-th sample previously resided</span></div>
<div class="line"><a id="l00194" name="l00194"></a><span class="lineno">  194</span>                cv_indices-&gt;second[ j ] = fold; <span class="comment">//store the partition to which the (now) i-th sample gets assigned</span></div>
<div class="line"><a id="l00195" name="l00195"></a><span class="lineno">  195</span>                <span class="comment">// old: //(*cv_indices)[ oldPos ] = fold; //store in vector to recreate partition if desired</span></div>
<div class="line"><a id="l00196" name="l00196"></a><span class="lineno">  196</span>            }</div>
<div class="line"><a id="l00197" name="l00197"></a><span class="lineno">  197</span> </div>
<div class="line"><a id="l00198" name="l00198"></a><span class="lineno">  198</span>            <span class="comment">//if all elements for the current batch are found, create it</span></div>
<div class="line"><a id="l00199" name="l00199"></a><span class="lineno">  199</span>            <span class="keywordflow">if</span> (batchElements[fold].size() == batchSizes[batchNumber]) {</div>
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno">  200</span>                newSet.<a class="code hl_function" href="group__shark__globals.html#ga192f5eced10acf38f3ae723a3c400d98">batch</a>(validationSetStart[fold]) = <a class="code hl_function" href="group__shark__globals.html#ga229ee860771047d3994953fdda9f5a6a" title="Creates a batch given a set of indices.">subBatch</a>(setView,batchElements[fold]);</div>
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno">  201</span>                batchElements[fold].clear();</div>
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno">  202</span>                ++validationSetStart[fold];</div>
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno">  203</span>            }</div>
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno">  204</span> </div>
<div class="line"><a id="l00205" name="l00205"></a><span class="lineno">  205</span>            fold = (fold+1) % numberOfPartitions;</div>
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno">  206</span> </div>
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno">  207</span>            j++;</div>
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno">  208</span>        }</div>
<div class="line"><a id="l00209" name="l00209"></a><span class="lineno">  209</span>    }</div>
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno">  210</span>    <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>( j == numInputs );</div>
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno">  211</span> </div>
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno">  212</span>    <span class="comment">//swap old and new set</span></div>
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno">  213</span>    <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(set, newSet);</div>
<div class="line"><a id="l00214" name="l00214"></a><span class="lineno">  214</span> </div>
<div class="line"><a id="l00215" name="l00215"></a><span class="lineno">  215</span>    <span class="comment">//create folds</span></div>
<div class="line"><a id="l00216" name="l00216"></a><span class="lineno">  216</span>    <span class="keywordflow">return</span> <a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt;(set,partitionStart);</div>
<div class="line"><a id="l00217" name="l00217"></a><span class="lineno">  217</span> </div>
<div class="line"><a id="l00218" name="l00218"></a><span class="lineno">  218</span>}</div>
<div class="line"><a id="l00219" name="l00219"></a><span class="lineno">  219</span>}<span class="comment">//namespace detail</span></div>
<div class="line"><a id="l00220" name="l00220"></a><span class="lineno">  220</span><span class="comment"></span> </div>
<div class="line"><a id="l00221" name="l00221"></a><span class="lineno">  221</span><span class="comment">/**</span></div>
<div class="line"><a id="l00222" name="l00222"></a><span class="lineno">  222</span><span class="comment"> * \ingroup shark_globals</span></div>
<div class="line"><a id="l00223" name="l00223"></a><span class="lineno">  223</span><span class="comment"> *</span></div>
<div class="line"><a id="l00224" name="l00224"></a><span class="lineno">  224</span><span class="comment"> * @{</span></div>
<div class="line"><a id="l00225" name="l00225"></a><span class="lineno">  225</span><span class="comment"> */</span></div>
<div class="line"><a id="l00226" name="l00226"></a><span class="lineno">  226</span><span class="comment"></span> </div>
<div class="line"><a id="l00227" name="l00227"></a><span class="lineno">  227</span><span class="comment">//! \brief Create a partition for cross validation</span></div>
<div class="line"><a id="l00228" name="l00228"></a><span class="lineno">  228</span><span class="comment">//!</span></div>
<div class="line"><a id="l00229" name="l00229"></a><span class="lineno">  229</span><span class="comment">//! The subset each training examples belongs to</span></div>
<div class="line"><a id="l00230" name="l00230"></a><span class="lineno">  230</span><span class="comment">//! is drawn independently and uniformly distributed.</span></div>
<div class="line"><a id="l00231" name="l00231"></a><span class="lineno">  231</span><span class="comment">//! For every partition, all but one subset form the</span></div>
<div class="line"><a id="l00232" name="l00232"></a><span class="lineno">  232</span><span class="comment">//! training set, while the remaining one is used for</span></div>
<div class="line"><a id="l00233" name="l00233"></a><span class="lineno">  233</span><span class="comment">//! validation. The partitions can be accessed using</span></div>
<div class="line"><a id="l00234" name="l00234"></a><span class="lineno">  234</span><span class="comment">//! getCVPartitionName</span></div>
<div class="line"><a id="l00235" name="l00235"></a><span class="lineno">  235</span><span class="comment">//!</span></div>
<div class="line"><a id="l00236" name="l00236"></a><span class="lineno">  236</span><span class="comment">//! \param set the input data for which the new partitions are created</span></div>
<div class="line"><a id="l00237" name="l00237"></a><span class="lineno">  237</span><span class="comment">//! \param numberOfPartitions  number of partitions to create</span></div>
<div class="line"><a id="l00238" name="l00238"></a><span class="lineno">  238</span><span class="comment">//! \param batchSize  maximum batch size</span></div>
<div class="line"><a id="l00239" name="l00239"></a><span class="lineno">  239</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> I,<span class="keyword">class</span> L&gt;</div>
<div class="foldopen" id="foldopen00240" data-start="{" data-end="}">
<div class="line"><a id="l00240" name="l00240"></a><span class="lineno"><a class="line" href="group__shark__globals.html#gac32dddc7b7c3eaa8779dc244c6142eef">  240</a></span><a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt; <a class="code hl_function" href="group__shark__globals.html#gac32dddc7b7c3eaa8779dc244c6142eef" title="Create a partition for cross validation.">createCVIID</a>(<a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;</a> &amp;set,</div>
<div class="line"><a id="l00241" name="l00241"></a><span class="lineno">  241</span>        std::size_t numberOfPartitions,</div>
<div class="line"><a id="l00242" name="l00242"></a><span class="lineno">  242</span>        std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>=<a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;I&gt;::DefaultBatchSize</a>) {</div>
<div class="line"><a id="l00243" name="l00243"></a><span class="lineno">  243</span>    std::vector&lt;std::size_t&gt; indices(set.<a class="code hl_function" href="group__shark__globals.html#ga5333445992cd6b14392cd80a1ab5403c" title="Returns the total number of elements.">numberOfElements</a>());</div>
<div class="line"><a id="l00244" name="l00244"></a><span class="lineno">  244</span>    <span class="keywordflow">for</span> (std::size_t i=0; i != set.<a class="code hl_function" href="group__shark__globals.html#ga5333445992cd6b14392cd80a1ab5403c" title="Returns the total number of elements.">numberOfElements</a>(); i++)</div>
<div class="line"><a id="l00245" name="l00245"></a><span class="lineno">  245</span>        indices[i] = <a class="code hl_function" href="namespaceshark_1_1random.html#aa64d4174eaf7111b03e0504eaa56b666" title="Draws a discrete number in {low,low+1,...,high} by drawing random numbers from rng.">random::discrete</a>(<a class="code hl_variable" href="namespaceshark_1_1random.html#ab5c1547eee483974d008d43f621a2234">random::globalRng</a>, std::size_t(0), numberOfPartitions - 1);</div>
<div class="line"><a id="l00246" name="l00246"></a><span class="lineno">  246</span>    <span class="keywordflow">return</span> <a class="code hl_function" href="group__shark__globals.html#gaab4c1c3153591bc8ae8130df6a84c65c" title="Create a partition for cross validation from indices.">createCVIndexed</a>(set,numberOfPartitions,indices,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>);</div>
<div class="line"><a id="l00247" name="l00247"></a><span class="lineno">  247</span>}</div>
</div>
<div class="line"><a id="l00248" name="l00248"></a><span class="lineno">  248</span><span class="comment"></span> </div>
<div class="line"><a id="l00249" name="l00249"></a><span class="lineno">  249</span><span class="comment">//! \brief Create a partition for cross validation</span></div>
<div class="line"><a id="l00250" name="l00250"></a><span class="lineno">  250</span><span class="comment">//!</span></div>
<div class="line"><a id="l00251" name="l00251"></a><span class="lineno">  251</span><span class="comment">//! Every subset contains (approximately) the same</span></div>
<div class="line"><a id="l00252" name="l00252"></a><span class="lineno">  252</span><span class="comment">//! number of elements. For every partition, all</span></div>
<div class="line"><a id="l00253" name="l00253"></a><span class="lineno">  253</span><span class="comment">//! but one subset form the training set, while the</span></div>
<div class="line"><a id="l00254" name="l00254"></a><span class="lineno">  254</span><span class="comment">//! remaining one is used for validation. The partitions</span></div>
<div class="line"><a id="l00255" name="l00255"></a><span class="lineno">  255</span><span class="comment">//! can be accessed using getCVPartitionName</span></div>
<div class="line"><a id="l00256" name="l00256"></a><span class="lineno">  256</span><span class="comment">//!</span></div>
<div class="line"><a id="l00257" name="l00257"></a><span class="lineno">  257</span><span class="comment">//! \param numberOfPartitions  number of partitions to create</span></div>
<div class="line"><a id="l00258" name="l00258"></a><span class="lineno">  258</span><span class="comment">//! \param set the input data from which to draw the partitions</span></div>
<div class="line"><a id="l00259" name="l00259"></a><span class="lineno">  259</span><span class="comment">//! \param batchSize  maximum batch size</span></div>
<div class="line"><a id="l00260" name="l00260"></a><span class="lineno">  260</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> I,<span class="keyword">class</span> L&gt;</div>
<div class="foldopen" id="foldopen00261" data-start="{" data-end="}">
<div class="line"><a id="l00261" name="l00261"></a><span class="lineno"><a class="line" href="group__shark__globals.html#gac5ab39c050dd915797e37fa421db33fd">  261</a></span><a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt; <a class="code hl_function" href="group__shark__globals.html#gac5ab39c050dd915797e37fa421db33fd" title="Create a partition for cross validation.">createCVSameSize</a>(<a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;</a> &amp;set,std::size_t numberOfPartitions,std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;::DefaultBatchSize</a>) {</div>
<div class="line"><a id="l00262" name="l00262"></a><span class="lineno">  262</span>    std::size_t numInputs = set.<a class="code hl_function" href="group__shark__globals.html#ga5333445992cd6b14392cd80a1ab5403c" title="Returns the total number of elements.">numberOfElements</a>();</div>
<div class="line"><a id="l00263" name="l00263"></a><span class="lineno">  263</span> </div>
<div class="line"><a id="l00264" name="l00264"></a><span class="lineno">  264</span>    <span class="comment">//calculate the number of validation examples for every partition</span></div>
<div class="line"><a id="l00265" name="l00265"></a><span class="lineno">  265</span>    std::vector&lt;std::size_t&gt; validationSize(numberOfPartitions);</div>
<div class="line"><a id="l00266" name="l00266"></a><span class="lineno">  266</span>    std::size_t inputsForValidation = numInputs / numberOfPartitions;</div>
<div class="line"><a id="l00267" name="l00267"></a><span class="lineno">  267</span>    std::size_t leftOver = numInputs - inputsForValidation * numberOfPartitions;</div>
<div class="line"><a id="l00268" name="l00268"></a><span class="lineno">  268</span>    <span class="keywordflow">for</span> (std::size_t i = 0; i != numberOfPartitions; i++) {</div>
<div class="line"><a id="l00269" name="l00269"></a><span class="lineno">  269</span>        std::size_t vs=inputsForValidation+(i&lt;leftOver);</div>
<div class="line"><a id="l00270" name="l00270"></a><span class="lineno">  270</span>        validationSize[i] =vs;</div>
<div class="line"><a id="l00271" name="l00271"></a><span class="lineno">  271</span>    }</div>
<div class="line"><a id="l00272" name="l00272"></a><span class="lineno">  272</span> </div>
<div class="line"><a id="l00273" name="l00273"></a><span class="lineno">  273</span>    <span class="comment">//calculate the size of batches for every validation part and their total number</span></div>
<div class="line"><a id="l00274" name="l00274"></a><span class="lineno">  274</span>    std::vector&lt;std::size_t&gt; partitionStart;</div>
<div class="line"><a id="l00275" name="l00275"></a><span class="lineno">  275</span>    std::vector&lt;std::size_t&gt; batchSizes;</div>
<div class="line"><a id="l00276" name="l00276"></a><span class="lineno">  276</span>    detail::batchPartitioning(validationSize,partitionStart,batchSizes,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>);</div>
<div class="line"><a id="l00277" name="l00277"></a><span class="lineno">  277</span> </div>
<div class="line"><a id="l00278" name="l00278"></a><span class="lineno">  278</span>    set.<a class="code hl_function" href="group__shark__globals.html#ga298a81625c3bcd482c3b68daf815c70b" title="Reorders the batch structure in the container to that indicated by the batchSizes vector.">repartition</a>(batchSizes);</div>
<div class="line"><a id="l00279" name="l00279"></a><span class="lineno">  279</span>    set.<a class="code hl_function" href="group__shark__globals.html#ga96ea65352abe5e2c0787e4154a48972f" title="shuffles all elements in the entire dataset (that is, also across the batches)">shuffle</a>();</div>
<div class="line"><a id="l00280" name="l00280"></a><span class="lineno">  280</span> </div>
<div class="line"><a id="l00281" name="l00281"></a><span class="lineno">  281</span>    <a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt; folds(set,partitionStart);</div>
<div class="line"><a id="l00282" name="l00282"></a><span class="lineno">  282</span>    <span class="keywordflow">return</span> folds;<span class="comment">//set;</span></div>
<div class="line"><a id="l00283" name="l00283"></a><span class="lineno">  283</span>}</div>
</div>
<div class="line"><a id="l00284" name="l00284"></a><span class="lineno">  284</span> </div>
<div class="line"><a id="l00285" name="l00285"></a><span class="lineno">  285</span><span class="comment"></span> </div>
<div class="line"><a id="l00286" name="l00286"></a><span class="lineno">  286</span><span class="comment">//! \brief Create a partition for cross validation</span></div>
<div class="line"><a id="l00287" name="l00287"></a><span class="lineno">  287</span><span class="comment">//!</span></div>
<div class="line"><a id="l00288" name="l00288"></a><span class="lineno">  288</span><span class="comment">//! Every subset contains (approximately) the same</span></div>
<div class="line"><a id="l00289" name="l00289"></a><span class="lineno">  289</span><span class="comment">//! number of elements. For every partition, all</span></div>
<div class="line"><a id="l00290" name="l00290"></a><span class="lineno">  290</span><span class="comment">//! but one subset form the training set, while the</span></div>
<div class="line"><a id="l00291" name="l00291"></a><span class="lineno">  291</span><span class="comment">//! remaining one is used for validation.</span></div>
<div class="line"><a id="l00292" name="l00292"></a><span class="lineno">  292</span><span class="comment">//!</span></div>
<div class="line"><a id="l00293" name="l00293"></a><span class="lineno">  293</span><span class="comment">//! \param numberOfPartitions  number of partitions to create</span></div>
<div class="line"><a id="l00294" name="l00294"></a><span class="lineno">  294</span><span class="comment">//! \param set the input data from which to draw the partitions</span></div>
<div class="line"><a id="l00295" name="l00295"></a><span class="lineno">  295</span><span class="comment">//! \param batchSize  maximum batch size</span></div>
<div class="line"><a id="l00296" name="l00296"></a><span class="lineno">  296</span><span class="comment">//! \param cv_indices if not NULL [default]: for each element, store the fold it is assigned to; this can be used to later/externally recreate the fold via createCVIndexed</span></div>
<div class="line"><a id="l00297" name="l00297"></a><span class="lineno">  297</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> I&gt;</div>
<div class="foldopen" id="foldopen00298" data-start="{" data-end="}">
<div class="line"><a id="l00298" name="l00298"></a><span class="lineno"><a class="line" href="group__shark__globals.html#gabb5bec2fca9d1eaa2ea58c75d36d1195">  298</a></span><a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,unsigned int&gt;</a> &gt; <a class="code hl_function" href="group__shark__globals.html#gabb5bec2fca9d1eaa2ea58c75d36d1195" title="Create a partition for cross validation.">createCVSameSizeBalanced</a> (</div>
<div class="line"><a id="l00299" name="l00299"></a><span class="lineno">  299</span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,unsigned int&gt;</a> &amp;set,</div>
<div class="line"><a id="l00300" name="l00300"></a><span class="lineno">  300</span>    std::size_t numberOfPartitions,</div>
<div class="line"><a id="l00301" name="l00301"></a><span class="lineno">  301</span>    std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>=<a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;I&gt;::DefaultBatchSize</a>,</div>
<div class="line"><a id="l00302" name="l00302"></a><span class="lineno">  302</span>    <a class="code hl_typedef" href="namespaceshark.html#a26c31934671564b8b69e260e23be0b90" title="auxiliary typedef for createCVSameSizeBalanced and createCVFullyIndexed, stores location index in the...">RecreationIndices</a> * cv_indices = NULL <span class="comment">//if not NULL: for each element, store the fold it is assigned to; this can be used to later/externally recreate the fold via createCVIndexed</span></div>
<div class="line"><a id="l00303" name="l00303"></a><span class="lineno">  303</span>){</div>
<div class="line"><a id="l00304" name="l00304"></a><span class="lineno">  304</span>    <a class="code hl_class" href="classshark_1_1_data_view.html" title="Constant time Element-Lookup for Datasets.">DataView&lt;LabeledData&lt;I,unsigned int&gt;</a> &gt; setView(set);</div>
<div class="line"><a id="l00305" name="l00305"></a><span class="lineno">  305</span>    std::size_t numInputs = setView.<a class="code hl_function" href="classshark_1_1_data_view.html#a71ba14d4f067dc437d6683dac9982f77">size</a>();</div>
<div class="line"><a id="l00306" name="l00306"></a><span class="lineno">  306</span>    std::size_t numClasses = <a class="code hl_function" href="group__shark__globals.html#ga1fee3b5830ae11a78109e8c0265c6569" title="Return the number of classes of a set of class labels with unsigned int label encoding.">numberOfClasses</a>(set);</div>
<div class="line"><a id="l00307" name="l00307"></a><span class="lineno">  307</span> </div>
<div class="line"><a id="l00308" name="l00308"></a><span class="lineno">  308</span> </div>
<div class="line"><a id="l00309" name="l00309"></a><span class="lineno">  309</span>    <span class="comment">//find members of each class</span></div>
<div class="line"><a id="l00310" name="l00310"></a><span class="lineno">  310</span>    std::vector&lt; std::vector&lt;std::size_t&gt; &gt; members(numClasses);</div>
<div class="line"><a id="l00311" name="l00311"></a><span class="lineno">  311</span>    <span class="keywordflow">for</span> (std::size_t i = 0; i != numInputs; i++) {</div>
<div class="line"><a id="l00312" name="l00312"></a><span class="lineno">  312</span>        members[setView[i].label].push_back(i);</div>
<div class="line"><a id="l00313" name="l00313"></a><span class="lineno">  313</span>    }</div>
<div class="line"><a id="l00314" name="l00314"></a><span class="lineno">  314</span>    <span class="keywordflow">return</span> detail::createCVSameSizeBalanced(set, numberOfPartitions, members, <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>, cv_indices);</div>
<div class="line"><a id="l00315" name="l00315"></a><span class="lineno">  315</span> </div>
<div class="line"><a id="l00316" name="l00316"></a><span class="lineno">  316</span>}</div>
</div>
<div class="line"><a id="l00317" name="l00317"></a><span class="lineno">  317</span><span class="comment"></span> </div>
<div class="line"><a id="l00318" name="l00318"></a><span class="lineno">  318</span><span class="comment">//! \brief Create a partition for cross validation without changing the dataset</span></div>
<div class="line"><a id="l00319" name="l00319"></a><span class="lineno">  319</span><span class="comment">//!</span></div>
<div class="line"><a id="l00320" name="l00320"></a><span class="lineno">  320</span><span class="comment">//! This method behaves similar to createCVIID</span></div>
<div class="line"><a id="l00321" name="l00321"></a><span class="lineno">  321</span><span class="comment">//! with the difference that batches are not reordered. Thus the batches</span></div>
<div class="line"><a id="l00322" name="l00322"></a><span class="lineno">  322</span><span class="comment">//! are only rearranged randomly in folds, but the dataset itself is not changed.</span></div>
<div class="line"><a id="l00323" name="l00323"></a><span class="lineno">  323</span><span class="comment">//!</span></div>
<div class="line"><a id="l00324" name="l00324"></a><span class="lineno">  324</span><span class="comment">//! \param numberOfPartitions  number of partitions to create</span></div>
<div class="line"><a id="l00325" name="l00325"></a><span class="lineno">  325</span><span class="comment">//! \param set the input data from which to draw the partitions</span></div>
<div class="line"><a id="l00326" name="l00326"></a><span class="lineno">  326</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> I, <span class="keyword">class</span> L&gt;</div>
<div class="foldopen" id="foldopen00327" data-start="{" data-end="}">
<div class="line"><a id="l00327" name="l00327"></a><span class="lineno"><a class="line" href="group__shark__globals.html#gaa79ee91055e415b81c7b6b14dd89c065">  327</a></span><a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt; <a class="code hl_function" href="group__shark__globals.html#gaa79ee91055e415b81c7b6b14dd89c065" title="Create a partition for cross validation without changing the dataset.">createCVBatch</a> (</div>
<div class="line"><a id="l00328" name="l00328"></a><span class="lineno">  328</span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;</a> <span class="keyword">const</span>&amp; set,</div>
<div class="line"><a id="l00329" name="l00329"></a><span class="lineno">  329</span>    std::size_t numberOfPartitions</div>
<div class="line"><a id="l00330" name="l00330"></a><span class="lineno">  330</span>){</div>
<div class="line"><a id="l00331" name="l00331"></a><span class="lineno">  331</span>    std::vector&lt;std::size_t&gt; indizes(set.<a class="code hl_function" href="group__shark__globals.html#gaca4b1e6083184385dba76a21b4c1d42b" title="Returns the number of batches of the set.">numberOfBatches</a>());</div>
<div class="line"><a id="l00332" name="l00332"></a><span class="lineno">  332</span>    <span class="keywordflow">for</span>(std::size_t i= 0; i != set.<a class="code hl_function" href="group__shark__globals.html#gaca4b1e6083184385dba76a21b4c1d42b" title="Returns the number of batches of the set.">numberOfBatches</a>(); ++i)</div>
<div class="line"><a id="l00333" name="l00333"></a><span class="lineno">  333</span>        indizes[i] = i;</div>
<div class="line"><a id="l00334" name="l00334"></a><span class="lineno">  334</span>    <a class="code hl_function" href="namespaceshark.html#af2ba61b9ed8b5072db8ce9582dcb94b0" title="random_shuffle algorithm which stops after acquiring the random subsequence for [begin,...">shark::shuffle</a>(indizes.begin(),indizes.end(), <a class="code hl_variable" href="namespaceshark_1_1random.html#ab5c1547eee483974d008d43f621a2234">random::globalRng</a>);</div>
<div class="line"><a id="l00335" name="l00335"></a><span class="lineno">  335</span>    </div>
<div class="line"><a id="l00336" name="l00336"></a><span class="lineno">  336</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="group__shark__globals.html#gaee99a1f7070bf91bd40cd660fc9411b4">LabeledData&lt;I,L&gt;::IndexSet</a> IndexSet;</div>
<div class="line"><a id="l00337" name="l00337"></a><span class="lineno">  337</span>    </div>
<div class="line"><a id="l00338" name="l00338"></a><span class="lineno">  338</span>    std::vector&lt;IndexSet&gt; folds;</div>
<div class="line"><a id="l00339" name="l00339"></a><span class="lineno">  339</span>    std::size_t partitionSize = set.<a class="code hl_function" href="group__shark__globals.html#gaca4b1e6083184385dba76a21b4c1d42b" title="Returns the number of batches of the set.">numberOfBatches</a>()/numberOfPartitions;</div>
<div class="line"><a id="l00340" name="l00340"></a><span class="lineno">  340</span>    std::size_t remainder = set.<a class="code hl_function" href="group__shark__globals.html#gaca4b1e6083184385dba76a21b4c1d42b" title="Returns the number of batches of the set.">numberOfBatches</a>() - partitionSize*numberOfPartitions;</div>
<div class="line"><a id="l00341" name="l00341"></a><span class="lineno">  341</span>    std::vector&lt;std::size_t&gt;::iterator pos = indizes.begin();</div>
<div class="line"><a id="l00342" name="l00342"></a><span class="lineno">  342</span>    <span class="keywordflow">for</span>(std::size_t i = 0; i!= numberOfPartitions; ++i){</div>
<div class="line"><a id="l00343" name="l00343"></a><span class="lineno">  343</span>        std::size_t size = partitionSize;</div>
<div class="line"><a id="l00344" name="l00344"></a><span class="lineno">  344</span>        <span class="keywordflow">if</span>(remainder&gt; 0){</div>
<div class="line"><a id="l00345" name="l00345"></a><span class="lineno">  345</span>            ++size;</div>
<div class="line"><a id="l00346" name="l00346"></a><span class="lineno">  346</span>            --remainder;</div>
<div class="line"><a id="l00347" name="l00347"></a><span class="lineno">  347</span>        }</div>
<div class="line"><a id="l00348" name="l00348"></a><span class="lineno">  348</span>        folds.push_back(IndexSet(pos,pos+size));</div>
<div class="line"><a id="l00349" name="l00349"></a><span class="lineno">  349</span>        pos+=size;</div>
<div class="line"><a id="l00350" name="l00350"></a><span class="lineno">  350</span>    }</div>
<div class="line"><a id="l00351" name="l00351"></a><span class="lineno">  351</span>    <span class="keywordflow">return</span> <a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt;(set,folds);</div>
<div class="line"><a id="l00352" name="l00352"></a><span class="lineno">  352</span>}</div>
</div>
<div class="line"><a id="l00353" name="l00353"></a><span class="lineno">  353</span><span class="comment"></span> </div>
<div class="line"><a id="l00354" name="l00354"></a><span class="lineno">  354</span><span class="comment">//! \brief Create a partition for cross validation from indices</span></div>
<div class="line"><a id="l00355" name="l00355"></a><span class="lineno">  355</span><span class="comment">//!</span></div>
<div class="line"><a id="l00356" name="l00356"></a><span class="lineno">  356</span><span class="comment">//! Create a partition from indices. The indices vector for each sample states of what</span></div>
<div class="line"><a id="l00357" name="l00357"></a><span class="lineno">  357</span><span class="comment">//! validation partition that sample should become a member. In other words, the index</span></div>
<div class="line"><a id="l00358" name="l00358"></a><span class="lineno">  358</span><span class="comment">//! maps a sample to a validation partition, meaning that it will become a part of the</span></div>
<div class="line"><a id="l00359" name="l00359"></a><span class="lineno">  359</span><span class="comment">//! training partition for all other folds.</span></div>
<div class="line"><a id="l00360" name="l00360"></a><span class="lineno">  360</span><span class="comment">//!</span></div>
<div class="line"><a id="l00361" name="l00361"></a><span class="lineno">  361</span><span class="comment">//! \param set partitions will be subsets of this set</span></div>
<div class="line"><a id="l00362" name="l00362"></a><span class="lineno">  362</span><span class="comment">//! \param numberOfPartitions  number of partitions to create</span></div>
<div class="line"><a id="l00363" name="l00363"></a><span class="lineno">  363</span><span class="comment">//! \param indices             partition indices of the examples in [0, ..., numberOfPartitions[.</span></div>
<div class="line"><a id="l00364" name="l00364"></a><span class="lineno">  364</span><span class="comment">//! \param batchSize  maximum batch size</span></div>
<div class="line"><a id="l00365" name="l00365"></a><span class="lineno">  365</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> I,<span class="keyword">class</span> L&gt;</div>
<div class="foldopen" id="foldopen00366" data-start="{" data-end="}">
<div class="line"><a id="l00366" name="l00366"></a><span class="lineno"><a class="line" href="group__shark__globals.html#gaab4c1c3153591bc8ae8130df6a84c65c">  366</a></span><a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt; <a class="code hl_function" href="group__shark__globals.html#gaab4c1c3153591bc8ae8130df6a84c65c" title="Create a partition for cross validation from indices.">createCVIndexed</a>(</div>
<div class="line"><a id="l00367" name="l00367"></a><span class="lineno">  367</span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;</a> &amp;set,</div>
<div class="line"><a id="l00368" name="l00368"></a><span class="lineno">  368</span>    std::size_t numberOfPartitions,</div>
<div class="line"><a id="l00369" name="l00369"></a><span class="lineno">  369</span>    std::vector&lt;std::size_t&gt; indices,</div>
<div class="line"><a id="l00370" name="l00370"></a><span class="lineno">  370</span>    std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>=<a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;I&gt;::DefaultBatchSize</a></div>
<div class="line"><a id="l00371" name="l00371"></a><span class="lineno">  371</span>) {</div>
<div class="line"><a id="l00372" name="l00372"></a><span class="lineno">  372</span>    std::size_t numInputs = set.<a class="code hl_function" href="group__shark__globals.html#ga5333445992cd6b14392cd80a1ab5403c" title="Returns the total number of elements.">numberOfElements</a>();</div>
<div class="line"><a id="l00373" name="l00373"></a><span class="lineno">  373</span>    <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(indices.size() == numInputs);</div>
<div class="line"><a id="l00374" name="l00374"></a><span class="lineno">  374</span>    <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(numberOfPartitions == *std::max_element(indices.begin(),indices.end())+1);</div>
<div class="line"><a id="l00375" name="l00375"></a><span class="lineno">  375</span> </div>
<div class="line"><a id="l00376" name="l00376"></a><span class="lineno">  376</span>    <span class="comment">//calculate the size of validation partitions</span></div>
<div class="line"><a id="l00377" name="l00377"></a><span class="lineno">  377</span>    std::vector&lt;std::size_t&gt; validationSize(numberOfPartitions,0);</div>
<div class="line"><a id="l00378" name="l00378"></a><span class="lineno">  378</span>    <span class="keywordflow">for</span> (std::size_t input = 0; input != numInputs; input++) {</div>
<div class="line"><a id="l00379" name="l00379"></a><span class="lineno">  379</span>        validationSize[indices[input]]++;</div>
<div class="line"><a id="l00380" name="l00380"></a><span class="lineno">  380</span>    }</div>
<div class="line"><a id="l00381" name="l00381"></a><span class="lineno">  381</span> </div>
<div class="line"><a id="l00382" name="l00382"></a><span class="lineno">  382</span>    <span class="comment">//calculate the size of batches for every validation part and their total number</span></div>
<div class="line"><a id="l00383" name="l00383"></a><span class="lineno">  383</span>    std::vector&lt;std::size_t&gt; partitionStart;</div>
<div class="line"><a id="l00384" name="l00384"></a><span class="lineno">  384</span>    std::vector&lt;std::size_t&gt; batchSizes;</div>
<div class="line"><a id="l00385" name="l00385"></a><span class="lineno">  385</span>    std::size_t numBatches = detail::batchPartitioning(validationSize,partitionStart,batchSizes,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>);</div>
<div class="line"><a id="l00386" name="l00386"></a><span class="lineno">  386</span> </div>
<div class="line"><a id="l00387" name="l00387"></a><span class="lineno">  387</span>    <span class="comment">//construct a new set with the correct batch format from the old set</span></div>
<div class="line"><a id="l00388" name="l00388"></a><span class="lineno">  388</span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;</a> newSet(numBatches);</div>
<div class="line"><a id="l00389" name="l00389"></a><span class="lineno">  389</span>    <a class="code hl_class" href="classshark_1_1_data_view.html" title="Constant time Element-Lookup for Datasets.">DataView&lt;LabeledData&lt;I,L&gt;</a> &gt; setView(set); <span class="comment">//fast access to single elements of the original set</span></div>
<div class="line"><a id="l00390" name="l00390"></a><span class="lineno">  390</span>    std::vector&lt;std::size_t&gt; validationSetStart = partitionStart; <span class="comment">//current index for the batch of every partition</span></div>
<div class="line"><a id="l00391" name="l00391"></a><span class="lineno">  391</span>    std::vector&lt;std::vector&lt;std::size_t&gt; &gt; batchElements(numberOfPartitions);</div>
<div class="line"><a id="l00392" name="l00392"></a><span class="lineno">  392</span>    <span class="keywordflow">for</span> (std::size_t input = 0; input != numInputs; input++) {</div>
<div class="line"><a id="l00393" name="l00393"></a><span class="lineno">  393</span>        std::size_t partition = indices[input];</div>
<div class="line"><a id="l00394" name="l00394"></a><span class="lineno">  394</span>        batchElements[partition].push_back(input);</div>
<div class="line"><a id="l00395" name="l00395"></a><span class="lineno">  395</span> </div>
<div class="line"><a id="l00396" name="l00396"></a><span class="lineno">  396</span>        <span class="comment">//if all elements for the current batch are found, create it</span></div>
<div class="line"><a id="l00397" name="l00397"></a><span class="lineno">  397</span>        std::size_t batchNumber = validationSetStart[partition];</div>
<div class="line"><a id="l00398" name="l00398"></a><span class="lineno">  398</span>        <span class="keywordflow">if</span> (batchElements[partition].size() == batchSizes[batchNumber]) {</div>
<div class="line"><a id="l00399" name="l00399"></a><span class="lineno">  399</span>            newSet.<a class="code hl_function" href="group__shark__globals.html#ga192f5eced10acf38f3ae723a3c400d98">batch</a>(validationSetStart[partition]) = <a class="code hl_function" href="group__shark__globals.html#ga229ee860771047d3994953fdda9f5a6a" title="Creates a batch given a set of indices.">subBatch</a>(setView,batchElements[partition]);</div>
<div class="line"><a id="l00400" name="l00400"></a><span class="lineno">  400</span>            batchElements[partition].clear();</div>
<div class="line"><a id="l00401" name="l00401"></a><span class="lineno">  401</span>            ++validationSetStart[partition];</div>
<div class="line"><a id="l00402" name="l00402"></a><span class="lineno">  402</span>        }</div>
<div class="line"><a id="l00403" name="l00403"></a><span class="lineno">  403</span>    }</div>
<div class="line"><a id="l00404" name="l00404"></a><span class="lineno">  404</span>    <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(set, newSet);</div>
<div class="line"><a id="l00405" name="l00405"></a><span class="lineno">  405</span>    <span class="comment">//now we only need to create the subset itself</span></div>
<div class="line"><a id="l00406" name="l00406"></a><span class="lineno">  406</span>    <span class="keywordflow">return</span> <a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt;(set,partitionStart);</div>
<div class="line"><a id="l00407" name="l00407"></a><span class="lineno">  407</span>}</div>
</div>
<div class="line"><a id="l00408" name="l00408"></a><span class="lineno">  408</span> </div>
<div class="line"><a id="l00409" name="l00409"></a><span class="lineno">  409</span> </div>
<div class="line"><a id="l00410" name="l00410"></a><span class="lineno">  410</span><span class="comment"></span> </div>
<div class="line"><a id="l00411" name="l00411"></a><span class="lineno">  411</span><span class="comment">//! \brief Create a partition for cross validation from indices for both ordering and partitioning.</span></div>
<div class="line"><a id="l00412" name="l00412"></a><span class="lineno">  412</span><span class="comment">//!</span></div>
<div class="line"><a id="l00413" name="l00413"></a><span class="lineno">  413</span><span class="comment">//! Create a partition from indices. There is one index vector assigning an order</span></div>
<div class="line"><a id="l00414" name="l00414"></a><span class="lineno">  414</span><span class="comment">//! to the samples, and another one assigning each sample to a validation partition.</span></div>
<div class="line"><a id="l00415" name="l00415"></a><span class="lineno">  415</span><span class="comment">//! That is, given a dataset set, and at the i-th processing step, this function puts</span></div>
<div class="line"><a id="l00416" name="l00416"></a><span class="lineno">  416</span><span class="comment">//! the order_indices[i]-th sample into the partition_indices[i]-th partition. The</span></div>
<div class="line"><a id="l00417" name="l00417"></a><span class="lineno">  417</span><span class="comment">//! order_indices part of the above procedure matters if both an inner and</span></div>
<div class="line"><a id="l00418" name="l00418"></a><span class="lineno">  418</span><span class="comment">//! outer partition are to be recreated: for the inner partition to be recreated, too,</span></div>
<div class="line"><a id="l00419" name="l00419"></a><span class="lineno">  419</span><span class="comment">//! the outer partition must be recreated in the same order, not just partitioned into</span></div>
<div class="line"><a id="l00420" name="l00420"></a><span class="lineno">  420</span><span class="comment">//! the same splits.</span></div>
<div class="line"><a id="l00421" name="l00421"></a><span class="lineno">  421</span><span class="comment">//!</span></div>
<div class="line"><a id="l00422" name="l00422"></a><span class="lineno">  422</span><span class="comment">//! \param set                  partitions will be subsets of this set</span></div>
<div class="line"><a id="l00423" name="l00423"></a><span class="lineno">  423</span><span class="comment">//! \param numberOfPartitions   number of partitions to create</span></div>
<div class="line"><a id="l00424" name="l00424"></a><span class="lineno">  424</span><span class="comment">//! \param indices              stores location index in the first and partition index in the second vector</span></div>
<div class="line"><a id="l00425" name="l00425"></a><span class="lineno">  425</span><span class="comment">//! \param batchSize            maximum batch size</span></div>
<div class="line"><a id="l00426" name="l00426"></a><span class="lineno">  426</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> I,<span class="keyword">class</span> L&gt;</div>
<div class="foldopen" id="foldopen00427" data-start="{" data-end="}">
<div class="line"><a id="l00427" name="l00427"></a><span class="lineno"><a class="line" href="group__shark__globals.html#ga44f464d4c5fd227a608980516f3aeaf7">  427</a></span><a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt; <a class="code hl_function" href="group__shark__globals.html#ga44f464d4c5fd227a608980516f3aeaf7" title="Create a partition for cross validation from indices for both ordering and partitioning.">createCVFullyIndexed</a>(</div>
<div class="line"><a id="l00428" name="l00428"></a><span class="lineno">  428</span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;</a> &amp;set,</div>
<div class="line"><a id="l00429" name="l00429"></a><span class="lineno">  429</span>    std::size_t numberOfPartitions,</div>
<div class="line"><a id="l00430" name="l00430"></a><span class="lineno">  430</span>    <a class="code hl_typedef" href="namespaceshark.html#a26c31934671564b8b69e260e23be0b90" title="auxiliary typedef for createCVSameSizeBalanced and createCVFullyIndexed, stores location index in the...">RecreationIndices</a> indices,</div>
<div class="line"><a id="l00431" name="l00431"></a><span class="lineno">  431</span>    std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>=<a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;I&gt;::DefaultBatchSize</a></div>
<div class="line"><a id="l00432" name="l00432"></a><span class="lineno">  432</span>) {</div>
<div class="line"><a id="l00433" name="l00433"></a><span class="lineno">  433</span>    std::size_t numInputs = set.<a class="code hl_function" href="group__shark__globals.html#ga5333445992cd6b14392cd80a1ab5403c" title="Returns the total number of elements.">numberOfElements</a>();</div>
<div class="line"><a id="l00434" name="l00434"></a><span class="lineno">  434</span>    <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(indices.first.size() == numInputs);</div>
<div class="line"><a id="l00435" name="l00435"></a><span class="lineno">  435</span>    <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(indices.second.size() == numInputs);</div>
<div class="line"><a id="l00436" name="l00436"></a><span class="lineno">  436</span>    <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(numberOfPartitions == *std::max_element(indices.second.begin(),indices.second.end())+1);</div>
<div class="line"><a id="l00437" name="l00437"></a><span class="lineno">  437</span> </div>
<div class="line"><a id="l00438" name="l00438"></a><span class="lineno">  438</span>    <span class="comment">//calculate the size of validation partitions</span></div>
<div class="line"><a id="l00439" name="l00439"></a><span class="lineno">  439</span>    std::vector&lt;std::size_t&gt; validationSize(numberOfPartitions,0);</div>
<div class="line"><a id="l00440" name="l00440"></a><span class="lineno">  440</span>    <span class="keywordflow">for</span> (std::size_t input = 0; input != numInputs; input++) {</div>
<div class="line"><a id="l00441" name="l00441"></a><span class="lineno">  441</span>        validationSize[indices.second[input]]++;</div>
<div class="line"><a id="l00442" name="l00442"></a><span class="lineno">  442</span>    }</div>
<div class="line"><a id="l00443" name="l00443"></a><span class="lineno">  443</span> </div>
<div class="line"><a id="l00444" name="l00444"></a><span class="lineno">  444</span>    <span class="comment">//calculate the size of batches for every validation part and their total number</span></div>
<div class="line"><a id="l00445" name="l00445"></a><span class="lineno">  445</span>    std::vector&lt;std::size_t&gt; partitionStart;</div>
<div class="line"><a id="l00446" name="l00446"></a><span class="lineno">  446</span>    std::vector&lt;std::size_t&gt; batchSizes;</div>
<div class="line"><a id="l00447" name="l00447"></a><span class="lineno">  447</span>    std::size_t numBatches = detail::batchPartitioning(validationSize,partitionStart,batchSizes,<a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>);</div>
<div class="line"><a id="l00448" name="l00448"></a><span class="lineno">  448</span> </div>
<div class="line"><a id="l00449" name="l00449"></a><span class="lineno">  449</span>    <span class="comment">//construct a new set with the correct batch format from the old set</span></div>
<div class="line"><a id="l00450" name="l00450"></a><span class="lineno">  450</span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;I,L&gt;</a> newSet(numBatches);</div>
<div class="line"><a id="l00451" name="l00451"></a><span class="lineno">  451</span>    <a class="code hl_class" href="classshark_1_1_data_view.html" title="Constant time Element-Lookup for Datasets.">DataView&lt;LabeledData&lt;I,L&gt;</a> &gt; setView(set); <span class="comment">//fast access to single elements of the original set</span></div>
<div class="line"><a id="l00452" name="l00452"></a><span class="lineno">  452</span>    std::vector&lt;std::size_t&gt; validationSetStart = partitionStart; <span class="comment">//current index for the batch of every partition</span></div>
<div class="line"><a id="l00453" name="l00453"></a><span class="lineno">  453</span>    std::vector&lt;std::vector&lt;std::size_t&gt; &gt; batchElements(numberOfPartitions);</div>
<div class="line"><a id="l00454" name="l00454"></a><span class="lineno">  454</span>    <span class="keywordflow">for</span> (std::size_t input = 0; input != numInputs; input++) {</div>
<div class="line"><a id="l00455" name="l00455"></a><span class="lineno">  455</span>        std::size_t partition = indices.second[input]; <span class="comment">//the second vector&#39;s contents indicate the partition to assign each sample to.</span></div>
<div class="line"><a id="l00456" name="l00456"></a><span class="lineno">  456</span>        batchElements[partition].push_back( indices.first[input] ); <span class="comment">//the first vector&#39;s contents indicate from what original position to get the next sample.</span></div>
<div class="line"><a id="l00457" name="l00457"></a><span class="lineno">  457</span> </div>
<div class="line"><a id="l00458" name="l00458"></a><span class="lineno">  458</span>        <span class="comment">//if all elements for the current batch are found, create it</span></div>
<div class="line"><a id="l00459" name="l00459"></a><span class="lineno">  459</span>        std::size_t batchNumber = validationSetStart[partition];</div>
<div class="line"><a id="l00460" name="l00460"></a><span class="lineno">  460</span>        <span class="keywordflow">if</span> (batchElements[partition].size() == batchSizes[batchNumber]) {</div>
<div class="line"><a id="l00461" name="l00461"></a><span class="lineno">  461</span>            newSet.<a class="code hl_function" href="group__shark__globals.html#ga192f5eced10acf38f3ae723a3c400d98">batch</a>(validationSetStart[partition]) = <a class="code hl_function" href="group__shark__globals.html#ga229ee860771047d3994953fdda9f5a6a" title="Creates a batch given a set of indices.">subBatch</a>(setView,batchElements[partition]);</div>
<div class="line"><a id="l00462" name="l00462"></a><span class="lineno">  462</span>            batchElements[partition].clear();</div>
<div class="line"><a id="l00463" name="l00463"></a><span class="lineno">  463</span>            ++validationSetStart[partition];</div>
<div class="line"><a id="l00464" name="l00464"></a><span class="lineno">  464</span>        }</div>
<div class="line"><a id="l00465" name="l00465"></a><span class="lineno">  465</span>    }</div>
<div class="line"><a id="l00466" name="l00466"></a><span class="lineno">  466</span>    <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(set, newSet);</div>
<div class="line"><a id="l00467" name="l00467"></a><span class="lineno">  467</span>    <span class="comment">//now we only need to create the subset itself</span></div>
<div class="line"><a id="l00468" name="l00468"></a><span class="lineno">  468</span>    <span class="keywordflow">return</span> <a class="code hl_class" href="classshark_1_1_c_v_folds.html">CVFolds&lt;LabeledData&lt;I,L&gt;</a> &gt;(set,partitionStart);</div>
<div class="line"><a id="l00469" name="l00469"></a><span class="lineno">  469</span>}</div>
</div>
<div class="line"><a id="l00470" name="l00470"></a><span class="lineno">  470</span> </div>
<div class="line"><a id="l00471" name="l00471"></a><span class="lineno">  471</span> </div>
<div class="line"><a id="l00472" name="l00472"></a><span class="lineno">  472</span><span class="comment">// much more to come...</span></div>
<div class="line"><a id="l00473" name="l00473"></a><span class="lineno">  473</span><span class="comment"></span> </div>
<div class="line"><a id="l00474" name="l00474"></a><span class="lineno">  474</span><span class="comment">/** @}*/</span></div>
<div class="line"><a id="l00475" name="l00475"></a><span class="lineno">  475</span>}</div>
<div class="line"><a id="l00476" name="l00476"></a><span class="lineno">  476</span><span class="preprocessor">#endif</span></div>
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